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---
language:
- ar
datasets:
- ASTD
tags:
- labr
widget:
- text: "العنف والقتل في محيط العالم في زياده يوميا"
- text: "الصداقه تزرع الحياه ازهارا"
---
# BERT-ASTD Balanced
Arabic version bert model fine tuned on ASTD dataset balanced version to identify twitter sentiments in Arabic language MSA dialect .
## Data
The model were fine-tuned on ~63000 book reviews in arabic using bert large arabic
## Results
| class | precision | recall | f1-score | Support |
|----------|-----------|--------|----------|---------|
| 0 | 0.9328 | 0.9398 | 0.9363 | 133 |
| 1 | 0.9394 | 0.9323 | 0.9358 | 133 |
| Accuracy | | | 0.9361 | 266 |
## How to use
You can use these models by installing `torch` or `tensorflow` and Huggingface library `transformers`. And you can use it directly by initializing it like this:
```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model_name="mofawzy/BERT-ASTD"
model = AutoModelForSequenceClassification.from_pretrained(model_name,num_labels=2)
tokenizer = AutoTokenizer.from_pretrained(model_name)
```
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